ROLE OF VULNERABILITY AND SUSCEPTIBILITY
Environmental, socioeconomic, demographic, biological, cultural, and political factors contribute to malaria risk and vulnerability.
PEOPLE
People who are vulnerable to malaria are pregnant women and children under 5 particularly and people who lack immunity to malaria and have exposure to malaria endemic areas. Pregnancy reduces immunity to malaria making them more susceptible. There is a higher chance of them complications such as fetal anemia, stillbirth, spontaneous abortion, low birth weight and infant death. Children under 5 years affected by Malaria are accounted for higher number of deaths worldwide.
ROLE OF ENVIRONMENT
People residing in close proximity to streams, irrigation systems and abandoned gem pits, have an influence on malaria incidence. Vulnerability to malaria has a geographic aspect and adverse risk factors such as type of housing, economic activity and age distribution. The influence of control measures has to be taken account of in risk prediction. Climate can also have an influence on the exposure (e.g. irrigation practices) and on vulnerability (susceptibility is enhanced due to malnutrition during droughts) and on control programs (e.g. distribution of bed nets). Vulnerability assessment has to be conducted to delineate the geographic location of the epidemic prone populations along with other demographic and socio-economic characteristics that lead to susceptibility.
EARLY WARNING SYSTEMS
Climate monitoring and seasonal forecasts can be used to anticipate disease risk if the relationship between climate and disease is understood. Early detection and warning can be undertaken through disease surveillance, entomological monitoring (which provides a lead time of weeks), monitoring climatic and environmental variables (which gives a month lead time ) and the use of seasonal predictions of climatic and environmental variables up to 3 months ahead (which gives a lead time of up to 4 months). The longer lead times are achieved at the cost of accuracy and greater uncertainty but all of these predictions are useful for different disease control decisions